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callbk

finlight-mcp

search_articles

Find financial news articles enriched with sentiment scores and tagged companies. Filter by ticker, source, country, date, and language to get market-relevant insights.

Instructions

Search for financial news articles. Returns market-relevant news enriched with sentiment analysis and optional company entity tagging.

Key features:

  • Advanced query language with boolean operators (AND, OR, NOT) and field filters (ticker:AAPL, source:reuters.com)

  • Filter by stock tickers, countries, categories, sources, date ranges, and language

  • Each article includes sentiment analysis (positive/negative/neutral) with confidence scores

  • Optional full article content and tagged company entities (requires subscription)

Response includes: title, summary, publishDate, source, language, sentiment, confidence, and optionally content and companies array.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoEnd date for article search. Accepts YYYY-MM-DD format or full ISO 8601 datetime. Example: "2024-12-31"
fromNoStart date for article search. Accepts YYYY-MM-DD format or full ISO 8601 datetime. Example: "2024-01-01" or "2024-01-01T00:00:00Z"
pageNoPage number for pagination. Default: 1. Max offset (page * pageSize) is 10,000.
orderNoSort order for results. DESC = newest first (default), ASC = oldest first.
queryNoAdvanced query string supporting boolean operators and field filters. Examples: "Nvidia earnings", "(ticker:AAPL OR ticker:NVDA) AND NOT source:www.reuters.com", "CEO resignation AND ticker:TSLA"
orderByNoField to sort by. publishDate = when article was published (default), createdAt = when article was indexed.
sourcesNoLimit to specific news sources by domain. Overrides the default source set. Example: ["www.reuters.com", "www.bloomberg.com"]. Use list_sources to see all available sources.
tickersNoFilter articles mentioning specific stock tickers. Example: ["AAPL", "NVDA", "TSLA"]. Articles are tagged with companies using NLP entity recognition.
languageNoFilter by article language code. Default: "en". Other options: "de", "fr", "es", etc.
pageSizeNoNumber of articles per page. Range: 1-100. Default: 20
countriesNoFilter by ISO 3166-1 alpha-2 country codes of tagged companies. Example: ["US", "GB", "DE"] for US, UK, and German companies.
categoriesNoFilter by article categories. Available categories: markets, economy, business, politics, geopolitics, regulation, technology, energy, commodities, crypto, health, climate, security.
optInSourcesNoAdd additional sources to the default source set (instead of replacing it). Useful for including specialty sources.
excludeSourcesNoExclude specific sources from results. Example: ["www.foxbusiness.com"]
includeContentNoInclude full article text content in response. Requires a subscription plan with content access. Default: false
includeEntitiesNoInclude tagged company entities with details like ticker, exchange, sector, industry, ISIN codes, and OpenFIGI identifiers. Requires subscription. Default: false
excludeEmptyContentNoSkip articles where content scraping failed or is unavailable. Useful when includeContent is true.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden and does well by disclosing subscription requirements for content/entities, describing the response structure, and highlighting key behavioral features like advanced query syntax and default source handling. It does not explicitly state it is read-only, but the term 'search' implies a safe operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a clear opening sentence, a concise 'Key features' bullet list, and a response overview. Every sentence earns its place, providing a strong summary without unnecessary repetition or bloat, especially given the large number of parameters.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description gives a good high-level overview but lacks important details for a tool with zero required parameters—for example, the default behavior when no query is provided, or the default date range. It also does not mention how search results are ordered by default (though schema covers it). Given the complexity and absent output schema, it's adequate but has clear gaps around default behavior and edge cases.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description adds no significant new meaning beyond the schema; it repeats filter capabilities and mentions subscription requirements, which are already documented in the schema. It adds value in summarizing the query language but does not clarify any parameters beyond what schema descriptions already provide.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool searches for financial news articles with sentiment analysis and optional entity tagging. It distinguishes itself from sibling tools (get_article_by_link retrieves specific articles, list_sources lists sources) by emphasizing its broad search, filtering, and enrichment capabilities.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use this tool (searching with filters, sentiment, etc.), though it does not explicitly mention alternatives or exclusion criteria. It implies this is the go-to for article search rather than retrieving by link or listing sources.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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